1. Field of the Invention
The present invention generally relates to image processing and, more specifically, to a system and method for transforming fingerprint images to improve recognition by distortion removal.
2. Background Description
For many years, fingerprints have been used to identify individuals. There exist systems for accomplishing automatic authentication or identification of a person using images of the fingerprint. A fingerprint of a person comprises a distinctive and unique ridge pattern structure which allows for such identification of a person among millions. The image of a fingerprint can be recorded in one of a number of ways. Traditionally, fingerprints were recorded by inking the finger and rolling it in a controlled way across a piece of paper. Fingerprints can also be captured by dabbing the inked finger onto paper.
Non-ink processes have also been developed to leave a permanent record, and fingerprints left in sweat and natural oils on a variety of substances can also be enhanced and photographed.
More recently, automatic fingerprint identification (AFI) systems have been developed, and for quick capture of a fingerprint xe2x80x9clive scanxe2x80x9d devices have been used. These sensors, typically ultrasound, electronic or optical, can capture a fingerprint image directly from the finger without the intermediate paper or ink stage.
Regardless of how the fingerprint image is obtained, the AFI system is used to compare images and determine if a query print matches a stored print in a database. However, the process of imaging by any method inherently introduces a distortion into the representation. Since the distortion for the query print and database print cannot be exactly equal the distortion makes it hard to compare the fingerprints.
Distortion is introduced in a number of ways, but for most sensors it comes about by trying to capture an image of a surface in three dimensions with a two dimensional imaging device. As the finger is pressed against the paper or against the imaging device (typically an integrated circuit, prism or other optical element), the curved, elastic finger is compressed and its surface is deformed into a flat plane (in some cases a surface curved in one direction, but never a surface of the exact shape of the finger). This distortion can be minimized by trained personnel controlling the way the finger is dabbed or rolled, but because of the transformation from a three-dimensional surface to a two-dimensional surface, some distortion is inevitable, and the image will not be consistent when a subsequent print is taken of the same finger.
It is possible to scan the finger shape in free space, without pressing it against a flat surface (e.g., with a laser scanner, a binocular optical system, etc.), but there is still inherent variability in the image shape because the shape of the finger changes (depending on the current water content of the skin for instance).
Thus, it can be seen that fingerprint images are inherently variable because of distortions. These variations make the matching of two fingerprints difficult since two images of the same fingerprint will never be the same. It is thus hard to tell whether differences between two prints are due to noise processes like the distortion mentioned above, or due to a difference in identity between the fingers represented.
Previous AFI systems have not tackled the problem of distortion. While a trained professional fingerprint officer can make allowance for the presence of distortion, computer systems are misled by the distortion which changes the ridge spacings, the distances between features arid the relationships between features (e.g., points collinear on one image may not be on the next because of distortion).
Since AFI systems rely on this kind of representation of fingerprints (inter-feature relations, distances and ridge spacing), the distortion means that prints from the same finger do not look similar and the match between the prints may be overlooked. Historically, such systems have either relied on trained operators to reduce the distortion to a minimum, allowed multiple presentations of a finger to the device, with the hope that one with minimal distortion will be obtained, or the systems have been used in situations where errors are tolerated.
Each of these xe2x80x9csolutionsxe2x80x9d bypasses the real problem and has inherent disadvantages. Trained operators are expensive and defeat much of the object of automating the rest of the system. Multiple presentations are time consuming and annoying to the users, increase false acceptance error rates (allowing an impostor multiple attempts a being recognized) and increase wear on the sensor. Doing nothing about the problem lends to high error rates, either by rejecting legitimate matches, or if the system is made lax to avoid that problem, by falsely accepting more impostors.
It is therefore an object of the present invention to provide a system and method to reduce the amount of variation in a fingerprint image due to distortion from elastic deformation of the finger surface and projection onto a planar coordinate system.
The invention works by estimating the amount and extent of distortion, and inverting the process in a systematic way, so that:
1. the amount of distortion is minimized; and
2. the distortion present is consistent, so that different images of the same print will have very similar distortion and thus matching of the fingerprints will be reliable and unaffected by the distortion.
According to a preferred embodiment of the invention, there is provided a system for estimating the distortion present in a fingerprint which comprises a computer with one or more central processing units, one or more memories, and one or more input devices. An input device captures one or more images, and the captured image is converted into a representation of the locations of the fingerprint ridges or valleys. An estimating function estimates the distance between two ridges (valleys) on the image, and the estimates of the ridge distances are combined. Based on the combined estimates, the fingerprint image is transformed to remove estimated distortion.
The method according to the invention reduces the amount of distortion present in a fingerprint representation by first capturing a fingerprint image. The captured fingerprint image is distorted by the capture process. The captured fingerprint image is preprocessed, and information of the locations of ridges or valleys in the captured fingerprint image are extracted. The ridge or valley spacing throughout the captured fingerprint image is estimated, and based on this estimate, an average ridge or valley spacing in the captured fingerprint image is estimated. Then, localized warps in the captured fingerprint image are estimated to normalize ridge or valley spacing. Minutiae information from the captured fingerprint image is extracted, and local warps are applied to the estimated minutiae locations without distortion. Finally, existing minutiae matching algorithms are applied to establish fingerprint identity.